import seaborn as sns

titanic=sns.load_dataset("titanic")

titanic.head()

	survived	pclass	sex	age	sibsp	parch	fare	embarked	class	who	adult_male	deck	embark_town	alive	alone
0	0	3	male	22.0	1	0	7.2500	S	Third	man	True	NaN	Southampton	no	False
1	1	1	female	38.0	1	0	71.2833	C	First	woman	False	C	Cherbourg	yes	False
2	1	3	female	26.0	0	0	7.9250	S	Third	woman	False	NaN	Southampton	yes	True
3	1	1	female	35.0	1	0	53.1000	S	First	woman	False	C	Southampton	yes	False
4	0	3	male	35.0	0	0	8.0500	S	Third	man	True	NaN	Southampton	no	True

import plotly.express as px
import numpy as np

pip install plotly

Collecting plotly
  Downloading plotly-5.13.1-py2.py3-none-any.whl (15.2 MB)
     |████████████████████████████████| 15.2 MB 12.8 MB/s eta 0:00:01
Collecting tenacity>=6.2.0
  Downloading tenacity-8.2.2-py3-none-any.whl (24 kB)
Installing collected packages: tenacity, plotly
Successfully installed plotly-5.13.1 tenacity-8.2.2
Note: you may need to restart the kernel to use updated packages.

px.scatter(data_frame=titanic,x="age",y="fare")

Q2. Using the tips dataset in the Plotly library, plot a box plot using Plotly express.

tips = sns.load_dataset('tips')

tips

	total_bill	tip	sex	smoker	day	time	size
0	16.99	1.01	Female	No	Sun	Dinner	2
1	10.34	1.66	Male	No	Sun	Dinner	3
2	21.01	3.50	Male	No	Sun	Dinner	3
3	23.68	3.31	Male	No	Sun	Dinner	2
4	24.59	3.61	Female	No	Sun	Dinner	4
...	...	...	...	...	...	...	...
239	29.03	5.92	Male	No	Sat	Dinner	3
240	27.18	2.00	Female	Yes	Sat	Dinner	2
241	22.67	2.00	Male	Yes	Sat	Dinner	2
242	17.82	1.75	Male	No	Sat	Dinner	2
243	18.78	3.00	Female	No	Thur	Dinner	2

244 rows × 7 columns

df=px.data.tips()

fig=px.box(df,y="total_bill")
fig.show()

Q3. Using the tips dataset in the Plotly library, Plot a histogram for x= "sex" and y="total_bill" column in the tips dataset. Also, use the "smoker" column with the pattern_shape parameter and the "day" column with the color parameter.

import plotly.express as px
df=px.data.tips()

fig=px.histogram(df,x="sex",y="total_bill",color="day",pattern_shape="smoker")
fig.show()

Q4. Using the iris dataset in the Plotly library, Plot a scatter matrix plot, using the "species" column for the color parameter. Note: Use "sepal_length", "sepal_width", "petal_length", "petal_width" columns only with the dimensions parameter.

import plotly.express as px
df = px.data.iris()
fig=px.scatter_matrix(df,dimensions=["sepal_length","sepal_width","petal_length","petal_width"],
                      color="species")
fig.show()

Q5. What is Distplot? Using Plotly express, plot a distplot.

The displot figure factory display a combination of statistical representing of numerical data,such as histogram,kernel density estimation or normal curve,and rug plot.

The displot can composed of all or any combination of the following 3 components:- a)histogram b)curve c)rug plot

import plotly.figure_factory as ff
x=np.random.randn(1000)
hist_data=[x]
group_labels=['distplot']
fig=ff.create_distplot(hist_data,group_labels)
fig.show()